Cover Image

Assessing the effect of climate factors on dengue incidence via a generalized linear model

Changes in climate factors such as temperature, rainfall, humidity, and wind speed are natural processes that could significantly impact the incidence of infectious diseases. Dengue is a widespread disease that has often been documented when it comes to the impact of climate change. It has become a...

Full description

Saved in:
Bibliographic Details
Main Authors: Sulekan, Ayuna, Suhaila, Jamaludin, Abdul Wahid, Nurmarni Athirah
Format: Article
Language:English
Published: Scientific Research Publishing Inc. 2021
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/97371/1/AyunaSulekan2021_AssessingtheEffectofClimateFactors.pdf
http://eprints.utm.my/id/eprint/97371/
http://dx.doi.org/10.4236/ojapps.2021.104039
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.97371
record_format eprints
spelling my.utm.973712022-10-10T04:00:36Z http://eprints.utm.my/id/eprint/97371/ Assessing the effect of climate factors on dengue incidence via a generalized linear model Sulekan, Ayuna Suhaila, Jamaludin Abdul Wahid, Nurmarni Athirah QA Mathematics Changes in climate factors such as temperature, rainfall, humidity, and wind speed are natural processes that could significantly impact the incidence of infectious diseases. Dengue is a widespread disease that has often been documented when it comes to the impact of climate change. It has become a significant concern, especially for the Malaysian health authorities, due to its rapid spread and serious effects, leading to loss of life. Several statistical models were performed to identify climatic factors associated with infectious diseases. However, because of the complex and nonlinear interactions between climate variables and disease components, modelling their relationships have become the main challenge in climate-health studies. Hence, this study proposed a Generalized Linear Model (GLM) via Poisson and Negative Binomial to examine the effects of the climate factors on dengue incidence by considering the collinearity between variables. This study focuses on the dengue hot spots in Malaysia for the year 2014. Since there exists collinearity between climate factors, the analysis was done separately using three different models. The study revealed that rainfall, temperature, humidity, and wind speed were statistically significant with dengue incidence, and most of them shown a negative effect. Of all variables, wind speed has the most significant impact on dengue incidence. Having this kind of relationships, policymakers should formulate better plans such that precautionary steps can be taken to reduce the spread of dengue diseases. Scientific Research Publishing Inc. 2021-04 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/97371/1/AyunaSulekan2021_AssessingtheEffectofClimateFactors.pdf Sulekan, Ayuna and Suhaila, Jamaludin and Abdul Wahid, Nurmarni Athirah (2021) Assessing the effect of climate factors on dengue incidence via a generalized linear model. Open Journal of Applied Sciences, 11 (4). pp. 549-563. ISSN 2165-3917 http://dx.doi.org/10.4236/ojapps.2021.104039 DOI:10.4236/ojapps.2021.104039
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Sulekan, Ayuna
Suhaila, Jamaludin
Abdul Wahid, Nurmarni Athirah
Assessing the effect of climate factors on dengue incidence via a generalized linear model
description Changes in climate factors such as temperature, rainfall, humidity, and wind speed are natural processes that could significantly impact the incidence of infectious diseases. Dengue is a widespread disease that has often been documented when it comes to the impact of climate change. It has become a significant concern, especially for the Malaysian health authorities, due to its rapid spread and serious effects, leading to loss of life. Several statistical models were performed to identify climatic factors associated with infectious diseases. However, because of the complex and nonlinear interactions between climate variables and disease components, modelling their relationships have become the main challenge in climate-health studies. Hence, this study proposed a Generalized Linear Model (GLM) via Poisson and Negative Binomial to examine the effects of the climate factors on dengue incidence by considering the collinearity between variables. This study focuses on the dengue hot spots in Malaysia for the year 2014. Since there exists collinearity between climate factors, the analysis was done separately using three different models. The study revealed that rainfall, temperature, humidity, and wind speed were statistically significant with dengue incidence, and most of them shown a negative effect. Of all variables, wind speed has the most significant impact on dengue incidence. Having this kind of relationships, policymakers should formulate better plans such that precautionary steps can be taken to reduce the spread of dengue diseases.
format Article
author Sulekan, Ayuna
Suhaila, Jamaludin
Abdul Wahid, Nurmarni Athirah
author_facet Sulekan, Ayuna
Suhaila, Jamaludin
Abdul Wahid, Nurmarni Athirah
author_sort Sulekan, Ayuna
title Assessing the effect of climate factors on dengue incidence via a generalized linear model
title_short Assessing the effect of climate factors on dengue incidence via a generalized linear model
title_full Assessing the effect of climate factors on dengue incidence via a generalized linear model
title_fullStr Assessing the effect of climate factors on dengue incidence via a generalized linear model
title_full_unstemmed Assessing the effect of climate factors on dengue incidence via a generalized linear model
title_sort assessing the effect of climate factors on dengue incidence via a generalized linear model
publisher Scientific Research Publishing Inc.
publishDate 2021
url http://eprints.utm.my/id/eprint/97371/1/AyunaSulekan2021_AssessingtheEffectofClimateFactors.pdf
http://eprints.utm.my/id/eprint/97371/
http://dx.doi.org/10.4236/ojapps.2021.104039
_version_ 1748180450073903104
score 13.211869

Similar Items